Over the years, the increasing development of coastal areas has modified the quality of water and sediments as well as marine habitats. Ports, which are the main interfaces between cities and the sea, are primarily subjected to a multi-source of contamination due to intense anthropogenic activities. Their complex geometry and infrastructure (e.g., quays, channels, and docks) induce low circulation and stagnant waters which tend to enhance and to control the fate of contaminants. Given the tendency of pollutants to remain confined and settle on the bottom, the pollution generated within the ports is of grave concern. Then, improving water and sediment quality is of vital importance for the sustainable development of coastal waters.
In recent decades, managers have been under increasing pressure to demonstrate the environmental skills of the port they manage. Some studies focused on the effect of diffuse pollution originating from urban water runoffs and boat repair activities [1
] as well as accidental oil spills [3
]. Metal concentrations in water and sediments were also monitored and investigated [5
] but characterising the water quality of such areas is still a challenge as it requires many parameters.
Although ports are considered as low-energy systems, the hydrological pattern established within the port basin cannot be neglected in any study [7
]. The rate of renewal of a basin is useful information that provides a first-order description of its dynamics. Numerous transport timescales have been defined through the literature to quantify this renewal [8
]. With the growing use of numerical modelling, these water transport timescales are useful parameters to condense the considerable amount of data in intelligible and quantitative information [13
]. The most commonly used, “flushing time”, “residence time”, ”age”, and ”exposure time” have been applied in a wide range of studies all over the world [14
]. From the environmental port management point of view, these transport timescales offer an interesting indication of the spatial and temporal variability of the dynamic and of the susceptibility to pollution. However, such timescale descriptors need to be carefully employed because there is no real consensus on their application [11
After an expansion in 2014 (corresponding to the NE basin in Figure 1
), La Rochelle Marina, located in the southwestern part of France, is currently considered as the biggest marina on the European Atlantic coast. Despite the environmental policy and ecological awareness of the marina, equipment and maritime activities may be a source of the pollution [18
]. The main objective of this study is, therefore, to characterise the water renewal of La Rochelle Marina due to the horizontal and vertical variability of its currents. This contribution can be considered as a first scientific investigation because, even if the importance of such timescales is evident, no references or estimates were available in the literature for a similar marina.
To describe water renewal mechanisms accurately, we performed a large number of simulations with a 3D hydrodynamic model calibrated and validated in a previous study [19
]. The specificity of the model is to take into consideration the considerable number of structures floating in the marina (e.g., docks, boats). In this study, three timescales are compared (flushing time, residence time and exposure time) to find the most relevant parameter to describe water renewal of the domain. Besides, we estimated the return-flow in different ways, the fraction of water that leaves the marina at ebb tide before re-entering it at the next flood tide [20
], and its effect on the tidal flushing of the marina was analysed. The above-mentioned timescales and quantities were computed for different scenarios to characterise the influence of wind, tide and floating structures on the water renewal. In the next section, study site and numerical computations will be presented before introducing definitions and concepts of chosen timescales and quantities. In Section 3
, a Lagrangian validation is carried out while timescale results are shown in Section 4
and discussed in Section 5
3. Lagrangian Validation
In a previous study [19
], the validation of the model was done in term of water levels and currents intensity, at numerous locations, inside and outside the marina. Here, the simulated velocities and trajectories of particles are compared with the observational data collected by the drifting buoys. The analysis offered in this section gives a spatially continuous distribution of model skill in the upper layer of La Rochelle harbour and marina entrance. The Lagrangian time series of surface velocity allow evaluating the performance of the model to reproduce dispersion trends of surface waters, which differs from the Eulerian assessment commonly used in validation methodology.
In the framework of the study, several drifting buoys were released for a wide range of temporal and spatial scales. The drifters, manufactured by Pacific Gyres (Oceanside, CA, USA), are composed of a surface float with a diameter of 0.3 m and a drogue dimension of 1.2 m length. The buoy uses Iridium to send float positions with 5-min temporal resolution. First experiments involved their deployment at the marina entrance with less than 1-h transport while the following occurred more offshore for timescales reaching more than one day. The range of hydrodynamics and atmospheric conditions tested, and the settings of the experiments were resumed in Table 2
while the mean trajectories of each drifting buoy experiment were resumed in Figure 3
a. Because of maritime infrastructure and boat navigation, more release of drifting buoys was needed to track sufficient currents patterns inside the marina.
To facilitate the comparison, the real-time positions of the drifting buoys were averaged for each release while the positions of 10 simulated drifters were averaged for each corresponding release. Comparison is visible in Figure 3
and shows fair agreement between the observed and simulated circulation of the drifters. While the distance between simulated and observed drifters can reach 600 m after one day of release, the comparison indicates a good correlation in term of velocities and a 6 cms−1
Root-Mean-Squared-Discrepancy (hereafter RMSD). The meridional (V) and zonal (U) components of velocity also display a fair agreement but with less accuracy and consistency (Table 3
). Globally, drifter buoy trajectories are better reproduced in the bay than in the marina, in particular during calm weather conditions where RMSD reaches 0.01 ms−1
. The tide in the bay rapidly and homogeneously advected drifter buoys while complex currents and micro-scale structures at the western marina entrance caused the buoys to diverge from each other. The model is less effective at reproducing the currents at the marina entrance, but the RMSD and R2
results show a good reproducibility in particular concerning the meridional component of the velocity (Table 3
). First and last deployments are characterised by stronger winds and the presence of waves in the bay. As the waves and their effects (Stokes drifts, interaction wave-currents) are not implemented in this modelling study, the quality of predictions of the model is slightly decreased (Table 3
6. Conclusions and Perspectives
The purpose of the present study was to characterise the water renewal of La Rochelle marina under a complete range of weather-marine conditions. We mainly focused on the physical mechanisms allowing to describe the renewal, but the results obtained might provide sufficient material for future studies related to the monitoring of pollutants and biological/ecological applications. Pollution is one of the major threats to water quality in coastal areas and understanding the physical behaviour of such environments is the first step toward efficient management of the problem. The results provided in this paper enable us to identify the most vulnerable zones concerning accidental pollution, but they can also be useful for undertaking protection and management policies. Results emphasise the substantial variability of the water renewal depending on the weather-marine conditions and the location in the marina.
Two different approaches helped us determining the temporal and spatial renewal of waters in the marina. The computation of three water transport timescales (IFT, RT and ET) led to the estimation of the return-flow in the marina via the RFF and RC formulations. Based on their study and comparison, the main findings concerning the water renewal in the marina are:
The marina displays a strong horizontal variability of the renewal. The most confined waters are located in the south of the SE basin, while the NE basin is generally the most renewed.
Both the tide and wind substantially impact the water renewal of the marina. The transition from spring to neap tides significantly decreases the water renewal while the presence of the wind enhances it, in particular for west and south directions.
In the marina, physical processes responsible for the water renewal are generally more affected by the tidal phase than in its surrounding bay.
The influence of the wind is less significant in the marina than in the system bay-marina.
The water renewal is relatively homogeneous over the water column even with the effect of the wind (data not shown).
As shown by the study of RT, the Floating Structures (FS) particularly decreased the water renewal in the most sheltered parts (SE basin), but they also generally increase it in the most exposed parts of the marina (NE basin). The study of both ET and IFT showed that they do not alter the circulation significantly outside the marina and thus, slightly affect the return-flow in the marina.
The return-flow has been consistently represented both in a Lagrangian and Eulerian way. Its information is a relevant indication of the circulation processes occurring outside the marina. Without wind, return-flow in the marina is amplified by neap tides that generate significant trapping of the water masses at the scale of the bay. Both ET and IFT results showed that return-flow was a key parameter in the dynamics of water renewal in the marina.
The return-flow is very sensitive to the wind action and the trapping processes happening in the bay can be drastically reduced. Wind enhances the dispersion of water masses away from the bay and thus decreases the return-flow in the marina. Powerful west winds (15 ms−1), typical of winter conditions, can generate a near-zero return-flow.
Without wind, return-flow is amplified by neap tides that generates significant trapping.
Given the importance of the return-flow in the region of interest, we should point out that tracer mass and particles dispersion directly depend on the size of the computational domain [27
]. We assumed the latter to be sufficiently large enough not to affect the tracer mass and the behaviour of the particles used in the definition of the water transport timescales.
The use of only one transport timescale (IFT) enabled to thoroughly describe the renewal processes occurring in the marina but also between the marina and its local environment. This parameter is less sensitive to the tidal phase release moment than RT, displays less chaotic patterns than ET and RT and offers the possibility to compute the return-flow efficiently through the tidal prism method. However, the comparison with Lagrangian timescales allowed us to detail the physical processes responsible for the renewal and to assess the consistency of the results. It underlines the need to cross-reference complementary methods and also puts forward some methods employed to address questions in a wide range of scientific domains.
Future works should characterise the influence of freshwater inflow and waves. Indeed, many authors suggested the contribution of the freshwater to the enhancement of the renewal [47
]. Even if river influence is negligible in our area, intense rainy events can significantly affect the renewal times [75
]. Waves that can be energetic offshore can also modify the exchange efficiency [20
]. In the next study, the influence of dredging maintenance of the marina on the water renewal will be investigated. Indeed, the water depth was found to increase the water exchange [79
], and it could be interesting to identify the optimal depth to improve the water quality of the marina.